PCA (Principal Component Analysis) ko 60 seconds...

Principal Component Analysis Explained This is how we take messy, high-dimensional data and turn it into a few clean, meaningful patterns. PCA finds the directions where the data varies the most and rewrites each data point using those directions instead of raw features. That’s how we reduce noise, avoid scale problems, and make models easier to visualize and train. It’s not magic - it’s just a smarter way to look at the same data. #machinelearning #ml #python #code #techtok

How to Use PCA and PCR Analyses in Prism with Multivariable Data